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candidate, with a strong background in the development of machine learning methods for bioinformatics. The project focuses on the development of new neural network architectures to perform inference
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department and the Plant Reproductive Strategies (SRP) team. Our team focuses on the evolution of plant reproductive systems, using diverse approaches including theory, experimentation, bioinformatics, and
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applying bioinformatics tools capable of predicting protein aggregation and co-aggregation, followed by large-scale scanning of microbial proteomes against the human proteome. The objective
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ExperienceNone Additional Information Eligibility criteria • PhD in statistical genetics, bioinformatics, evolutionary genetics, or a related field (obtained or in progress) • Strong knowledge of statistical
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existing meta-genomes, using up-to-date bioinformatics tools. The postdoctoral associate will explore the genes and pathways associated to carbon and iron metabolism of heterotrophic prokaryotes using
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-synaptic elements Targeted genetic manipulations of the neurons studied Analytical activities Extraction and analysis of transcriptomic data (RNA-seq) from single cells Bioinformatic analyses related
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challenges Specific Requirements Desirable criteria Knowledge of bioinformatics or computational analysis Evidence of successful collaboration in multidisciplinary projects LanguagesENGLISHLevelExcellent
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contact Prof. Dr. Antonio del Sol (email address: ). Your profile Ph.D. degree in computational biology, bioinformatics, biology, computer science or related disciplines Strong computational skills
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the project's personalized treatment algorithms. For further information, please contact Prof. Dr. Antonio del Sol, antonio.delsol [at] uni.lu . Your profile Ph.D. degree in computational biology, bioinformatics
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to join the AI for Genome Interpretation (AI4GI) group at the IGMM (CNRS, Montpellier). The project is a collaboration between IGMM and IMAG, at the interface of genetics, bioinformatics, statistics